positional arguments:¶

file

File to be filtered

dset

optional - dataset(s) to filter (default: []).

options:¶

-h, --help

show this help message and exit

-f {lowpass_gaussian,highpass_gaussian,lowpass_avg,highpass_avg,sobel,roberts,canny,double_difference}

Filter type (default: lowpass_gaussian). Check Bekaert et al. (2020) for double_difference; Check scikit-image as below for the other filters:

http://scikit-image.org/docs/dev/api/skimage.filters.html

-p [FILTER_PAR ...], --filter_par [FILTER_PAR ...]

Filter parameters for filters. Default:

Sigma

for low/high pass gaussian filter, default: 3.0

Kernel Size

for low/high pass average filter, default: 5

Kernel Radius for double difference local and regional filters, default: 1 10

-o OUTFILE, --outfile OUTFILE

Output file name.

references:¶

Bekaert, David PS, et al. "InSAR-based detection method for mapping and monitoring slow-moving landslides in remote regions with steep and mountainous terrain: An application to Nepal." Remote Sensing of Environment 249 (2020), doi:10.1016/j.rse.2020.111983.

example:¶

spatial_filter.py

velocity.h5

spatial_filter.py

timeseries.h5 -f lowpass_avg -p 5

spatial_filter.py

velocity.h5 -f lowpass_avg -p 5

spatial_filter.py

velocity.h5 -f highpass_gaussian -p 3

spatial_filter.py

velocity.h5 -f sobel

spatial_filter.py

ifgramStack.h5 unwrapPhase

spatial_filter.py

ifgramStack.h5 unwrapPhase -f lowpass_avg -p 5

spatial_filter.py

ifgramStack.h5 unwrapPhase -f double_difference -p 1 10